Effective Resource Allocation and Job Scheduling Mechanisms for Load Sharing in a Computational Grid

2009 ◽  
pp. 31-40
Author(s):  
Kuo-Chan Huang ◽  
Po-Chi Shih ◽  
Yeh-Ching Chung
Keyword(s):  
Site Selection ◽  
System Performance ◽  
Job Scheduling ◽  
Load Sharing ◽  
Turnaround Time ◽  
Computational Grid ◽  
Grid Environment ◽  
Grid Environments ◽  
Scheduling Mechanisms ◽  
Average Turnaround Time

Most current grid environments are established through collaboration among a group of participating sites which volunteer to provide free computing resources. Therefore, feasible load sharing policies that benefit all sites are an important incentive for attracting computing sites to join and stay in a grid environment. Moreover, a grid environment is usually heterogeneous in nature at least for different computing speeds at different participating sites. This chapter explores the feasibility and effectiveness of load sharing activities in a heterogeneous computational grid. Several issues are discussed including site selection policies as well as feasible load sharing mechanisms. Promising policies are evaluated in a series of simulations based on workloads derived from real traces. The results show that grid computing is capable of significantly improving the overall system performance in terms of average turnaround time for user jobs.

Multi-Objective Scheduling for Parallel Jobs on Grid

2010 ◽  
Vol 439-440 ◽  
pp. 1281-1286 ◽  
Author(s):  
Peng Fei Liu ◽  
Shou Bin Dong
Keyword(s):  
Large Scale ◽  
Job Scheduling ◽  
Scheduling Algorithm ◽  
Turnaround Time ◽  
Experimental Result ◽  
Parallel Job Scheduling ◽  
Multi Objective ◽  
Parallel Jobs ◽  
Parallel Job ◽  
Average Turnaround Time

Focused on the complexity of the parallel job scheduling on heterogeneous Grid, the paper proposes a multi-objective optimization based scheduling algorithm. The algorithm first splits the parallel job up into a series of independent processes with constraints, and then adopts particles to represent the mapping of job-resource. Multi-objective PSO is employed to simultaneously optimize the scheduling objectives of throughput and average turnaround time. Experimental result indicates that the proposed approach is effective while dealing with large scale parallel jobs scheduling on heterogeneous Grid and outperforms other conventional algorithms.

GA Based Scheduling Model for Computational Grid to Minimize Turnaround Time

2009 ◽  
Vol 1 (4) ◽  
pp. 70-90 ◽  
Author(s):  
Zahid Raza ◽  
Deo P. Vidyarthi
Keyword(s):  
Genetic Algorithm ◽  
Natural Selection ◽  
Job Scheduling ◽  
Optimization Problems ◽  
Turnaround Time ◽  
Computational Grid ◽  
Hard Problem ◽  
Simulation Studies ◽  
Scheduling Model ◽  
Np Hard Problem

Scheduling on distributed systems is an NP hard problem and grid being a wide heterogeneous expandable system makes scheduling even a tougher job. Genetic algorithm, based on natural selection and evolution has gained popularity in recent times because of its effectiveness in handling optimization problems. In this article, a job-scheduling model for a computational grid with the objective of minimizing the turnaround time using genetic algorithm is proposed. The model evaluates various clusters in the grid to find the most suitable one with minimum turnaround time for the job-scheduling. Simulation studies compare the performance of this model with other similar models.

QoS-based Job Scheduling and Resource Management Strategies for Grid Computing

2011 ◽  
pp. 110-127
Author(s):  
Kuo-Chan Huang ◽  
Po-Chi Shih ◽  
Yeh-Ching Chung
Keyword(s):  
Resource Allocation ◽  
Quality Of Service ◽  
Job Scheduling ◽  
Performance Metrics ◽  
Management Strategies ◽  
Load Sharing ◽  
Computational Grid ◽  
Qos Performance ◽  
Grid Level

This chapter elaborates the quality of service (QoS) aspect of load sharing activities in a computational grid environment. Load sharing is achieved through appropriate job scheduling and resource allocation mechanisms. A computational grid usually consists of several geographically distant sites each with different amount of computing resources. Different types of grids might have different QoS requirements. In most academic or experimental grids the computing sites volunteer to join the grids and can freely decide to quit the grids at any time when they feel joining the grids bring them no benefits. Therefore, maintaining an appropriate QoS level becomes an important incentive to attract computing sites to join a grid and stay in it. This chapter explores the QoS issues in such type of academic and experimental grids. This chapter first defines QoS based performance metrics for evaluating job scheduling and resource allocation strategies. According to the QoS performance metrics appropriate grid-level load sharing strategies are developed. The developed strategies address both user-level and site-level QoS concerns. A series of simulation experiments were performed to evaluate the proposed strategies based on real and synthetic workloads.

Intelligent Randomize Round Robin for Cloud Computing

2013 ◽  
Vol 3 (1) ◽  
pp. 27-33
Author(s):  
Muneer O. Bani Yassein ◽  
Yaser M. Khamayseh ◽  
Ali M. Hatamleh
Keyword(s):  
Cloud Computing ◽  
Job Scheduling ◽  
Turnaround Time ◽  
Round Robin ◽  
Cloud Data Center ◽  
Cloud Data ◽  
Basic Infrastructure ◽  
Resources Sharing ◽  
Average Turnaround Time ◽  
Selection Of

Cloud computing is a recent scientific revolution in information technology, it is considered as the basic infrastructure of ubiquitous computing. It supports various features including, Internet based computing, and resources sharing. Delivery of services is provided to computers and other devices upon request. In other words, it is a technology based on the internet and central remote servers to maintain data and applications. This technology allows consumers and enterprises to use applications without the need of installing them or allowing access to their personal files at any computer with internet access. Among different users that may access the cloud data center, cloud computing must include job scheduling to organize and monitor these jobs, and to achieve fairness among all users. One of the most popular job scheduling algorithms is Round Robin (RR). This paper proposes an enhancement to the traditional RR, namely Randomized Round Robin (RRR). The enhanced version of RR algorithms is based on random selection for processes that come from different users to achieve near optimal selection of jobs to be served. A simulation has been carried out using CloudSim simulator V 3.0 to test the performance of the proposed scheme in terms of different evaluation metrics such as average throughput and average turnaround time.

Moldable Job Allocation for Handling Resource Fragmentation in Computational Grid

2011 ◽  
pp. 58-71
Author(s):  
Kuo-Chan Huang ◽  
Po-Chi Shih ◽  
Yeh-Ching Chung
Keyword(s):  
System Performance ◽  
Computational Grid ◽  
Grid Environment ◽  
Allocation Policy ◽  
Job Allocation ◽  
Parallel Jobs ◽  
Parallel Job ◽  
Resource Fragmentation ◽  
Job Scheduler ◽  
Grid Resources

In a computational Grid environment, a common practice is to try to allocate an entire parallel job onto a single participating site. Sometimes a parallel job, upon its submission, cannot fit in any single site due to the occupation of some resources by running jobs. How the job scheduler handles such situations is an important issue which has the potential to further improve the utilization of Grid resources, as well as the performance of parallel jobs. This paper adopts moldable job allocation policies to deal with such situations in a heterogeneous computational Grid environment. The proposed policies are evaluated through a series of simulations using real workload traces. The moldable job allocation policies are also compared to the multi-site co-allocation policy, which is another approach usually used to deal with the resource fragmentation issue. The results indicate that the proposed moldable job allocation policies can further improve the system performance of a heterogeneous computational Grid significantly.

QoS-Based Job Scheduling and Resource Management Strategies for Grid Computing

2012 ◽  
pp. 1315-1331
Author(s):  
Kuo-Chan Huang ◽  
Po-Chi Shih ◽  
Yeh-Ching Chung
Keyword(s):  
Resource Allocation ◽  
Quality Of Service ◽  
Job Scheduling ◽  
Performance Metrics ◽  
Management Strategies ◽  
Load Sharing ◽  
Computational Grid ◽  
Qos Performance ◽  
Grid Level

This chapter elaborates the quality of service (QoS) aspect of load sharing activities in a computational grid environment. Load sharing is achieved through appropriate job scheduling and resource allocation mechanisms. A computational grid usually consists of several geographically distant sites each with different amount of computing resources. Different types of grids might have different QoS requirements. In most academic or experimental grids the computing sites volunteer to join the grids and can freely decide to quit the grids at any time when they feel joining the grids bring them no benefits. Therefore, maintaining an appropriate QoS level becomes an important incentive to attract computing sites to join a grid and stay in it. This chapter explores the QoS issues in such type of academic and experimental grids. This chapter first defines QoS based performance metrics for evaluating job scheduling and resource allocation strategies. According to the QoS performance metrics appropriate grid-level load sharing strategies are developed. The developed strategies address both user-level and site-level QoS concerns. A series of simulation experiments were performed to evaluate the proposed strategies based on real and synthetic workloads.

scholarly journals Book Availability Revisited: Turnaround Time for Recalls versus Interlibrary Loans

2003 ◽  
Vol 64 (4) ◽  
pp. 283-299 ◽  
Author(s):  
David J. Gregory ◽  
Wayne A. Pedersen
Keyword(s):  
Real Time ◽  
Phase 1 ◽  
Academic Library ◽  
Turnaround Time ◽  
Phase 2 ◽  
Interlibrary Loan ◽  
Reasonable Alternative ◽  
Local Institution ◽  
Timely Access ◽  
Average Turnaround Time

Librarians typically view interlibrary loan (ILL) as a means of providing access to items not owned by the local institution. However, they are less likely to explore ILL’s potential in providing timely access to items locally owned, but temporarily unavailable, particularly in the case of monographs in circulation. In a two-part study, the authors test the assumption that, on average, locally owned books that a patron finds unavailable (due to checkout) can be obtained more quickly via recall than via ILL. Phase 1 of this study establishes an average turnaround time for circulation recalls in a large academic library for comparison with well-established turnaround times for ILL borrowing transactions. In Phase 2, a more rigorous paired study of recalls and ILL compares the ability of each system to handle identical requests in real time. Results demonstrate that, under some circumstances, ILL provides a reasonable alternative to the internal recall process. The findings also underscore the need for more holistic, interservice models for improving not just access, but also the timeliness of access, to monograph collections.

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